Abstract
A numerical method combining a gradient technique with the projection onto a linear manifold is proposed for solving systems of linear inequalities. It is shown that the method converges in a finite number of iterations and its running time is estimated as a polynomial in the space dimension and the number of inequalities in the system.
Similar content being viewed by others
REFERENCES
V. G. Karmanov, Mathematical Programming (Nauka, Moscow, 2000) [in Russian].
A. I. Golikov and Yu. G. Evtushenko, “Theorems of the alternative and their applications in numerical methods,” Comput. Math. Math. Phys. 43 (3), 338–358 (2003).
Y. G. Evtushenko and A. I. Golikov, “New perspective on the theorems of alternative,” in High Performance Algorithms and Software for Nonlinear Optimization (Springer, New York, 2003), pp. 227–241.
A. A. Tret’yakov, “A finite-termination gradient projection method for solving systems of linear inequalities,” Russ. J. Numer. Anal. Math. Model. 25 (3), 279–288 (2010).
A. Tret’yakov and E. Tyrtyshnikov, “Exact differentiable penalty for a problem of quadratic programming with the use of a gradient-projective method,” Russ. J. Numer. Anal. Math. Model. 30 (2), 121–128 (2015).
S. Smale, “Mathematical problems for the next century,” in Mathematics: Frontiers and Perspectives (Am. Math. Soc., Providence, RI, 2000), pp. 271–294.
O. L. Mangasarian, “A finite Newton method for classification problems,” Technical Report, 01-11 (Data Mining Institute, Computer Sciences Department, University of Wisconsin, Madison, Wisconsin, 2001), pp. 01–11.
O. L. Mangasarian, “A Newton method for linear programming,” J. Optim. Theory Appl. 121 (1), 1–18 (2004).
K. N. Belash and A. A. Tret’yakov, “Methods for solving degenerate problems,” USSR Comput. Math. Math. Phys. 28 (4), 90–94 (1988).
O. A. Brezhneva and A. A. Tret’yakov, “The P-factor-Lagrange methods for degenerate nonlinear programming,” Numer. Funct. Anal. Optim. 28 (9–10), 1051–1086 (2007).
O. A. Brezhneva, Yu. G. Evtushenko, and A. A. Tret’yakov, “The 2-factor method with a modified Lagrange function for degenerate constrained optimization problems,” Dokl. Math. 73 (3), 384–387 (2006).
J. L. Goffin, “On the non-polynomiality of the relaxation method for systems of linear inequalities,” Math. Program. 22 (1), 93–103 (1982).
F. Facchinei, A. Fischer, and C. Kanzow, “On the accurate identification of active constraints,” SIAM J. Optim. 9 (1), 14–32 (1998).
E. Szczepanik and A. Tret’yakov, “p-factor methods for nonregular inequality-constrained optimization problems,” Nonlinear Anal. 69 (12), 4241–4251 (2008).
S. J. Wright, “An algorithm for degenerate nonlinear programming with rapid local convergence,” SIAM J. Optim. 15 (3), 673–696 (2005).
A. Tret’yakov and E. E. Tyrtyshnikov, “A finite gradient-projective solver for a quadratic programming problem,” Russ. J. Numer. Anal. Math. Model. 28 (3), 289–300 (2013).
S. P. Han, Least-Squares Solution of Linear Inequalities (Wisconsin Univ.-Madison Mathematics Research Center, 1980), No. MRC-TSR-2141.
Funding
This work was supported by the Russian Foundation for Basic Research, grant no. 17-07-00510.
Author information
Authors and Affiliations
Corresponding authors
Additional information
Translated by I. Ruzanova
Rights and permissions
About this article
Cite this article
Evtushenko, Y.G., Tret’yakov, A.A. Locally Polynomial Method for Solving Systems of Linear Inequalities. Comput. Math. and Math. Phys. 60, 222–226 (2020). https://doi.org/10.1134/S0965542520020050
Received:
Revised:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1134/S0965542520020050